Optimal Configuration and Planning of Distributed Energy Systems Considering Renewable Energy Resources

With increasing electricity demand, conventional centralized power generation systems encounter numerous challenges, including transmission and distribution losses, limited capacity, and high operational costs. In response, distributed energy systems have emerged as a promising solution by enabling electricity generation in close proximity to consumption points. These systems leverage renewable energy sources and minimize energy losses during transmission, presenting a more sustainable and efficient alternative. By utilizing diverse energy sources such as solar thermal panels, photovoltaic systems, geothermal energy, distributed energy systems enhance overall efficiency, and reduce power losses during transmission as well as greenhouse gas emissions. This research endeavor presents a novel approach employing mixed-integer linear programming to optimize distributed energy systems. The proposed model facilitates the determination of optimal dimensions of technologies, including combined heat and power systems, boilers, electric chillers, and absorption chillers, while simultaneously minimizing total costs and greenhouse gas emissions and adhering to real-world constraints. The findings of this study are validated through a real-world numerical example, confirming the model’s efficiency in configuring and planning distributed energy systems optimally, thereby enhancing their operational performance.